Voice AI systems that combine speech recognition, LLM reasoning, retrieval, backend orchestration, and business integrations into one reliable conversational workflow.

These systems are designed for customer support, appointment booking, lead qualification, sales, operations, and internal business assistants.

• AI receptionists • Customer support agents • Appointment booking and scheduling • Outbound sales calls • Lead qualification • Internal operations assistants • FAQ automation with business knowledge • Voice-enabled CRM workflows

• Real-time speech-to-text pipelines • LLM-powered conversational reasoning • Natural text-to-speech responses • Conversation state management • Human escalation workflows • RAG-based knowledge retrieval • CRM and API integrations • Appointment booking workflows • Structured data collection during calls • Logging, monitoring, retries, and fallback handling

Depending on the project, I work with technologies such as OpenAI, Claude, ElevenLabs, Deepgram, Twilio, FastAPI, LangChain, and modern backend infrastructure.

The implementation is always chosen based on your workflow rather than forcing a specific technology.

Review the conversation workflow and business goals.

Design the conversation architecture and decision flow.

Build the voice pipeline and backend orchestration.

Connect business systems, APIs, or CRM platforms.

Test latency, interruption handling, and edge cases.

Deploy, monitor, and iterate based on real conversations.

I usually recommend launching one production workflow first before expanding to additional call scenarios.